DBMS > Ehcache vs. SAP HANA vs. SQream DB

System Properties Comparison Ehcache vs. SAP HANA vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

In-memory, column based data store. Available as appliance or cloud service

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

www.ehcache.org

www.sap.com/products/hana.html

sqream.com

Technical documentation

www.ehcache.org/documentation

help.sap.com/hana

docs.sqream.com

Developer

Terracotta Inc, owned by Software AG

SAP

SQream Technologies

Initial release

2009

2010

2017

Current release

3.10.0, March 2022

2.0 SPS07 (April 4, 2023), April 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

All OS with a Java VM

Appliance or cloud-service

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JCache

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Java

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

SQLScript, R

user defined functions in Python

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

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